/*!
\file
\brief Robust
\author Vasek Smidl 

 */

#include "estim/arx.h"
#include "robustlib.h"
#include <vector>
#include <iostream>
#include <fstream>
//#include <itpp/itsignal.h>
#include "windows.h"
#include "ddeml.h"
#include "stdio.h"

//#include "DDEClient.h"
//#include <conio.h>


using namespace itpp;
using namespace bdm;

//const int emlig_size = 2;
//const int utility_constant = 5;

const int max_model_order = 2;
const double apriorno     = 0.01;
const int max_window_size = 30;

class model
{
public:
	set<pair<int,int>> ar_components;

	// Best thing would be to inherit the two models from a single souce, this is planned, but now structurally
	// problematic.
	RARX* my_rarx; //vzmenovane parametre pre triedu model
	ARXwin* my_arx;

	bool has_constant;
	int  window_size;  //musi byt vacsia ako pocet krokov ak to nema ovplyvnit
	int  predicted_channel;
	mat* data_matrix;
	vec  predictions;
	char name[80];
	
	model(set<pair<int,int>> ar_components, //funkcie treidz model-konstruktor
		  bool robust, 
		  bool has_constant, 
		  int window_size, 
		  int predicted_channel,
		  mat* data_matrix)
	{
		this->ar_components.insert(ar_components.begin(),ar_components.end());

		strcpy(name,"M");

		for(set<pair<int,int>>::iterator ar_ref = ar_components.begin();ar_ref!=ar_components.end();ar_ref++)
		{
			char buffer1[2];
			char buffer2[2];
			itoa((*ar_ref).first,buffer1,10);
			itoa((*ar_ref).second,buffer2,10);

			strcat(name,buffer1);
			strcat(name,buffer2);
			strcat(name,"_");
		}

		this->has_constant      = has_constant;

		if(has_constant)
		{
			strcat(name,"C");
		}

		this->window_size       = window_size;
		this->predicted_channel = predicted_channel;
		this->data_matrix       = data_matrix;

		if(robust)
		{
			strcat(name,"R");

			if(has_constant)
			{
				my_rarx = new RARX(ar_components.size()+1,window_size,true,sqrt(2*apriorno),sqrt(2*apriorno),ar_components.size()+4);
				my_arx  = NULL;
			}
		else
			{
				my_rarx = new RARX(ar_components.size(),window_size,false,sqrt(2*apriorno),sqrt(2*apriorno),ar_components.size()+3);
				my_arx  = NULL;
			}
		}
		else
		{
			my_rarx = NULL;
			my_arx  = new ARXwin();
			mat V0;

			if(has_constant)
			{				
				V0  = apriorno * eye(ar_components.size()+2); //aj tu konst
				//V0(0,0) = 0;
				my_arx->set_constant(true);				
			}
			else
			{
				
				V0  = apriorno * eye(ar_components.size()+1);//menit konstantu
				//V0(0,1) = -0.01;
				//V0(1,0) = -0.01;
				my_arx->set_constant(false);				
				
			}

			my_arx->set_statistics(1, V0, V0.rows()+2); 			
			my_arx->set_parameters(window_size);
			my_arx->validate();

			vec mean = my_arx->posterior().mean();
			cout << mean << endl;
		}
	}

	void data_update(int time) //vlozime cas a ono vlozi do data_vector podmineky(conditions) a predikce, ktore pouzije do bayes
	{
		vec data_vector;
		for(set<pair<int,int>>::iterator ar_iterator = ar_components.begin();ar_iterator!=ar_components.end();ar_iterator++)
		{  
			data_vector.ins(data_vector.size(),(*data_matrix).get(ar_iterator->first,time-ar_iterator->second));
		}
		if(my_rarx!=NULL)
		{	
			data_vector.ins(0,(*data_matrix).get(predicted_channel,time));
			my_rarx->bayes(data_vector);
		}
		else
		{
			vec pred_vec;
			pred_vec.ins(0,(*data_matrix).get(predicted_channel,time));
			my_arx->bayes(pred_vec,data_vector);
		}
	}

	pair<vec,vec> predict(int sample_size, int time, itpp::Laplace_RNG* LapRNG)  //nerozumiem, ale vraj to netreba, nepouziva to
	{
		vec condition_vector;
		for(set<pair<int,int>>::iterator ar_iterator = ar_components.begin();ar_iterator!=ar_components.end();ar_iterator++)
		{
			condition_vector.ins(condition_vector.size(),(*data_matrix).get(ar_iterator->first,time-ar_iterator->second+1));
		}

		if(my_rarx!=NULL)
		{
			pair<vec,mat> imp_samples = my_rarx->posterior->sample(sample_size,false);

			//cout << imp_samples.first << endl;			
			
			vec sample_prediction;			
			for(int t = 0;t<sample_size;t++)
			{
				vec lap_sample = condition_vector;
				
				if(has_constant)
				{
					lap_sample.ins(lap_sample.size(),1.0);
				}
				
				lap_sample.ins(lap_sample.size(),(*LapRNG)());

				sample_prediction.ins(0,lap_sample*imp_samples.second.get_col(t));				
			}

			return pair<vec,vec>(imp_samples.first,sample_prediction);
		}	
		else
		{
			mat samples = my_arx->posterior().sample_mat(sample_size);			
			
			vec sample_prediction;
			for(int t = 0;t<sample_size;t++)
			{
				vec gau_sample = condition_vector;
				
				if(has_constant)
				{
					gau_sample.ins(gau_sample.size(),1.0);
				}
				
				gau_sample.ins(gau_sample.size(),randn());

				sample_prediction.ins(0,gau_sample*samples.get_col(t));				
			}

			return pair<vec,vec>(ones(sample_prediction.size()),sample_prediction);
		}
	
	}


	static set<set<pair<int,int>>> possible_models_recurse(int max_order,int number_of_channels)
	{
		set<set<pair<int,int>>> created_model_types;		

		if(max_order == 1)
		{			
			for(int channel = 0;channel<number_of_channels;channel++)
			{
				set<pair<int,int>> returned_type;
				returned_type.insert(pair<int,int>(channel,1));  
				created_model_types.insert(returned_type);
			}

			return created_model_types;
		}
		else
		{
			created_model_types = possible_models_recurse(max_order-1,number_of_channels);
			set<set<pair<int,int>>> returned_types;
			
			for(set<set<pair<int,int>>>::iterator model_ref = created_model_types.begin();model_ref!=created_model_types.end();model_ref++)
			{				
				
				for(int order = 1; order<=max_order; order++)
				{
					for(int channel = 0;channel<number_of_channels;channel++)
					{
						set<pair<int,int>> returned_type;
						pair<int,int> new_pair = pair<int,int>(channel,order);
						if(find((*model_ref).begin(),(*model_ref).end(),new_pair)==(*model_ref).end()) 
						{
							returned_type.insert((*model_ref).begin(),(*model_ref).end()); 
							returned_type.insert(new_pair);
							

							returned_types.insert(returned_type);							
						}
					}
				}
			}

			created_model_types.insert(returned_types.begin(),returned_types.end());

			return created_model_types;
		}		
	}
};




int main ( int argc, char* argv[] ) 
{
	vector<vector<string>> strings;

	char* file_string =  "C:\\results\\normalM"; // "C:\\dataADClosePercDiff"; //  

	char dfstring[80];
	strcpy(dfstring,file_string);
	strcat(dfstring,".txt");
	
	
	mat data_matrix;
	ifstream myfile(dfstring);
	if (myfile.is_open())
	{		
		string line;
		while(getline(myfile,line))
		{			
			vec data_vector;
			while(line.find(',') != string::npos) 
			{				
				int loc2 = line.find('\n');
				int loc  = line.find(',');
				data_vector.ins(data_vector.size(),atof(line.substr(0,loc).c_str()));				
				line.erase(0,loc+1);					
			}

			data_matrix.ins_row(data_matrix.rows(),data_vector);
		}		

		myfile.close();	
	}
	else
	{
		cout << "Can't open data file!" << endl;
	}

	set<pair<int,int>> model_type;
	model_type.insert(pair<int,int>(0,1));
	model_type.insert(pair<int,int>(0,2));

	vector<model*> models;

	ofstream myfilew;
		

	while(data_matrix.rows()!=0)
	{
		for(int i=0;i<models.size();i++)
		{
			delete models[i];
		}
		
		models.clear();
		models.push_back(new model(model_type,true,false,max_window_size,0,&data_matrix));
		models.push_back(new model(model_type,false,false,max_window_size,0,&data_matrix));

		for(int time = max_model_order;time<max_window_size;time++) //time<data_matrix.cols() 
		{		
			vec cur_res_lognc;
		
			vector<string> nazvy;
			for(vector<model*>::iterator model_ref = models.begin();model_ref!=models.end();model_ref++)
			{
				(*model_ref)->data_update(time);

				cout << "Updated:" << time << endl;	

				if(time == max_window_size-1)
				{
					char fstring[80];					
					strcpy(fstring,file_string);
					strcat(fstring,"ml");					
					strcat(fstring,(*model_ref)->name);
					strcat(fstring,".txt");

					vec coords;
					if((*model_ref)->my_arx!=NULL)
					{
						coords = (*model_ref)->my_arx->posterior().est_theta();
					}
					else
					{
						coords = (*model_ref)->my_rarx->posterior->minimal_vertex->get_coordinates();						
					}

					myfilew.open(fstring,ios::app);

					for(int i=0;i<coords.size();i++)
					{
						myfilew << coords.get(i) << ",";
					}
					myfilew << endl;

					myfilew.close();				
				}
			}
		}

		data_matrix.del_row(0);
	}
	


	

	return 0;
}